The Ultimate Hands-On Hadoop: Tame your Big Data!

Data Engineering and Hadoop tutorial with MapReduce, HDFS, Spark, Flink, Hive, HBase, MongoDB, Cassandra, Kafka + more!

4.4 ★★★★★189,046 studentsCreated by Frank Kane, Sundog Education by Frank Kane, Sundog Education TeamLast updated Nov 13, 2025🌐 English

What you'll learn

✓Design distributed systems that manage "big data" using Hadoop and related data engineering technologies.

✓Use HDFS and MapReduce for storing and analyzing data at scale.

✓Use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways.

✓Analyze relational data using Hive and MySQL

✓Analyze non-relational data using HBase, Cassandra, and MongoDB

✓Query data interactively with Drill, Phoenix, and Presto

✓Choose an appropriate data storage technology for your application

✓Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie.

✓Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume

✓Consume streaming data using Spark Streaming, Flink, and Storm

Requirements

•You will need access to a x86-based PC running 64-bit Windows, MacOS, or Linux with an Internet connection and at least 8GB of *free* (not total) RAM, if you want to participate in the hands-on activities and exercises. If your PC does not meet these requirements or you only have an M1-based Mac available, you can still follow along in the course without doing hands-on activities.

•Some activities will require some prior programming experience, preferably in Python or Scala.

•A basic familiarity with the Linux command line will be very helpful.